Graph Partitioning and Graph Clustering

Graph partitioning and graph clustering are ubiquitous subtasks in
many applications where graphs play an important role. Generally
speaking, both techniques aim at the identification of vertex subsets
with many internal and few external edges. To name only a few,
problems addressed by graph partitioning and graph clustering
algorithms are:

What are the communities within an (online) social network?

How do I speed up a numerical simulation by mapping it
efficiently onto a parallel computer?

How must components be organized on a computer chip
such that they can communicate efficiently with each other?

What are the segments of a digital image?

Which functions are certain genes (most likely) responsible
for?

The 10th DIMACS Implementation Challenge Workshop was devoted to
determining realistic performance of algorithms where worst case
analysis is overly pessimistic and probabilistic models are too
unrealistic. Articles in the volume describe and analyze various
experimental data with the goal of getting insight into realistic
algorithm performance in situations where analysis fails.

This book is published in cooperation with the Center for Discrete Mathematics and Theoretical Computer Science

Readership

Graduate students and research mathematicians interested in
graph theory and combinatorial algorithms.

Graph partitioning and graph clustering are ubiquitous subtasks in
many applications where graphs play an important role. Generally
speaking, both techniques aim at the identification of vertex subsets
with many internal and few external edges. To name only a few,
problems addressed by graph partitioning and graph clustering
algorithms are:

What are the communities within an (online) social network?

How do I speed up a numerical simulation by mapping it
efficiently onto a parallel computer?

How must components be organized on a computer chip
such that they can communicate efficiently with each other?

What are the segments of a digital image?

Which functions are certain genes (most likely) responsible
for?

The 10th DIMACS Implementation Challenge Workshop was devoted to
determining realistic performance of algorithms where worst case
analysis is overly pessimistic and probabilistic models are too
unrealistic. Articles in the volume describe and analyze various
experimental data with the goal of getting insight into realistic
algorithm performance in situations where analysis fails.

This book is published in cooperation with the Center for Discrete Mathematics and Theoretical Computer Science

Book Series Name:
Contemporary Mathematics

Volume:
588

Publication Month and Year:
2013-03-18

Copyright Year:
2013

Page Count:
240

Cover Type:
Softcover

Print ISBN-13:
978-0-8218-9038-7

Online ISBN 13:
978-0-8218-9869-7

Print ISSN:
0271-4132

Online ISSN:
0271-4132

Primary MSC:
05;
68

Textbook?:
false

Applied Math?:
true

MAA Book?:
false

Electronic Media?:
false

Apparel or Gift:
false

Publisher (non-AMS):
Published in cooperation with Center for Discrete Mathematics and Theoretical Computer Science